NeuralTrust AI Security Model Performance Report 2026

NeuralTrust's AI security models demonstrate high performance across various tasks, achieving ROC-AUC scores between 0.991 and 0.9997. The models excel in detecting jailbreak attempts, toxicity, indirect prompt injections, and moderating prompts across 13 topics, with particularly strong results in jailbreak detection (92% detection rate, 2.3% false-positive rate) and indirect prompt injection detection (99.8% detection rate, 0.6% false-positive rate). Compared to AWS Bedrock Guardrails and Azure AI Content Safety, NeuralTrust's models show significant advantages, particularly in handling complex attack families and multilingual capabilities across nine languages. The models undergo rigorous stress testing and continuous improvement through a closed-loop evaluation platform, ensuring they remain effective against adversarial attacks and dynamic threats in real-world applications.

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